How to bend down the environmental Kuznets curve: the significance of biomass energy

Sources of renewable energy have received wide attention in the literature because of serious threats to the environment. However, some renewable resources, including biomass energy role is debatable in the energy economics literature. This empirical work focuses to analyze the role of biomass energy in carbon dioxide (CO₂) emissions using the framework of the environmental Kuznets curve (EKC) in Pakistan over the period from 1980 to 2015. The bound testing approach suggests there is cointegration among study variables. The study uses an auto-regressive distributed lag model (ARDL) with a structural break in the series. To summarize the findings of the study, it can be inferred that biomass energy increase CO₂ emissions. In addition, biomass energy helps to form a U-shaped relationship between income and CO₂ emissions that support the EKC hypothesis. Also, the feedback hypothesis is found between biomass energy and CO₂ emissions. The findings would guide policymaker with practical guidelines to formulate policies to utilize a high amount of biomass energy in a sustainable manner.

     

Carbon dioxide emissions,output, and energy consumption categories in Algeria

This study examines the relation between CO₂ emissions, income, non-renewable, and renewable energy consumption in Algeria during the period extending from 1980 to 2011. Our work gives particular attention to the validity of environmental Kuznets curve (EKC) hypothesis. The autoregressive distributed lag (ARDL) with break point method outcome demonstrates the positive effect of non-renewable type of energy on CO₂ emissions consumption. On the contrary, the results reveal an insignificant effect of renewable energy on environment improvement. Moreover, the results accept the existence of EKC hypothesis but the highest gross domestic product value in logarithm scale of our data is inferior to the estimated turning point. Consequently, policy-makers in Algeria should expand the ratio of renewable energy and should decrease the quota of non-renewable energy consumption.     

The impact of environment degrading factors and remittances on health expenditure: an asymmetric ARDL and dynamic simulated ARDL approach

This paper investigates the impact of CO₂ emissions, air pollution (PM2.5) exposure, foreign remittances, energy consumption, renewable energy consumption, trade openness, and gross domestic product per capita on health expenditure in a panel of the 27 highest emitting countries from 2000 to 2019. Focusing on objectives, panel ARDL, and dynamic simulated ARDL models are used to examine the short-run and long-run impact of the variables on health expenditure. An asymmetric or nonlinear ARDL model is used to test the asymmetric effect of CO₂ emissions, air pollution exposure, and foreign remittance inflows on health expenditure. The results show that environment-degrading factors, remittances, and GDP per capita significantly impact health expenditure. There is an asymmetric effect of remittances, CO₂ emissions, and air pollution (PM2.5) exposure on health expenditure. Based on the results, the study suggests policymakers should make policies regarding environment-degrading elements as these factors cause huge increases in health spending in a country. Consumption of renewable energy helps reduce health expenditure as it does not cause environmental degradation, irrespective of other forms of energy, and it is suggested that policies relating to foreign remittance inflows should be encouraged and made efficient.

     

Do renewable energies contribute to enhancing environmental quality in Eastern Africa?

East Africa has enormous renewable energy potential, but only a small portion of it has been exploited, and little is known on its role in improving environmental quality. Thus, this study empirically examines the impact of renewable energy on the environment using ecological footprint (EF; positive indicator) and CO₂ emissions (negative indicator) as proxy indicators for environmental quality in a panel of ten East African countries from 1990 to 2015. These indicators were chosen due to their potential impact in the environment. The work used the pooled mean group (PMG) as the main panel estimator to determine the impact while controlling non-renewable energy consumption, GDP per capita, and foreign direct investment (FDI). PMG has been used as it forces the long-run coefficients to be equal across all panel groups. The findings show that in the long run, there is a significant negative relationship between CO₂ emissions and renewable energy consumption, as well as a significant positive relationship (with a low impact) between EF and renewable energy consumption, suggesting that renewable energy use enhances the area’s environmental quality. Also, results indicate that non-renewable energy use degrades environmental quality in both metrics, whereas GDP degrades environmental quality through CO₂ emissions and improves environmental quality through EF. This requires East African countries to focus a higher emphasis on accessible renewable energy sources to achieve quick and sustainable economic growth and minimize environmental effects. To accomplish this, strategic policies and legislation, as well as the promotion of green technology, are required.

     

Influencing factors of carbon emissions and their trends in China and India: a machine learning method

China and India are the largest coal consumers and the most populated countries in the world. With industrial and population growth, the need for energy has increased, which has inevitably led to an increase in carbon dioxide (CO₂) emissions because both countries depend on fossil fuel consumption. This paper investigates the impact of energy consumption, financial development (FD), gross domestic product (GDP), population, and renewable energy on CO₂ emissions. The study applies the long short-term memory (LSTM) method, a novel machine learning (ML) approach, to examine which influencing driver has the greatest and smallest impact on CO₂ emissions; correspondingly, this study builds a model for CO₂ emission reduction. Data collected between 1990 and 2014 were analyzed, and the results indicated that energy consumption had the greatest effect and renewable energy had the smallest impact on CO₂ emissions in both countries. Subsequently, we increased the renewable energy coefficient by one and decreased the energy consumption coefficient by one while keeping all other factors constant, and the results predicted with the LSTM model confirmed the significant reduction in CO₂ emissions. Finally, this study forecasted a CO₂ emission trend, with a slowdown predicted in China by 2022; however, CO₂ emission’s reduction is not possible in India until 2023. These results suggest that shifting from nonrenewable to renewable sources and lowering coal consumption can reduce CO₂ emissions without harming economic development.

     

The effects of economic growth and innovation on CO2 emissions in different regions

Economic growth and economic energy consumption have received greater attention due to its contribution to global CO₂ emissions in recent decades. The literature on CO₂ emissions and innovation for regional differences is very scanty as there is not enough study that considered different regions in a single analysis. We adopt a holistic approach by incorporating different regions so as to assess how innovation contributes to emission reduction. The study, therefore, examined the effects of innovation and economic growth on CO₂ emissions for 18 developed and developing countries over the period of 1990 to 2016. The study used panel technique capable of dealing with cross-section dependence effects: panel cross-sectional augmented Dickey-Fuller (CADF) unit root to determine the order of integration, Westerlund cointegration tests confirmed that the variables are co-integrated. We employed panel fully modified ordinary least square (FMOLS) and panel dynamic ordinary least square (DOLS) to estimate the long-run relationship. The results show that energy consumption increases CO₂ emissions at all panel levels. However, innovation reduces CO₂ emissions in G6 while it increases emissions in the MENA and the BRICS countries. Environmental Kuznets curve (EKC) hypothesis is valid for the BRICS. The pollution haven hypothesis (PHH) and pollution halo effect were confirmed at different panel levels. Based on the findings different policy recommendations are proposed.

     

Biofuel consumption,biodiversity, and the environmental Kuznets curve: trivariate analysis in a panel of biofuel consuming countries

This study examined the relationship between biofuel consumption, forest biodiversity, and a set of national scale indicators of per capita income, foreign direct investment (FDI) inflows, trade openness, and population density with a panel data of 12 biofuels consuming countries for a period of 2000 to 2013. The study used Global Environmental Facility (GEF) biodiversity benefits index and forest biodiversity index in an environmental Kuznets curve (EKC) framework. The results confirmed an inverted U-shaped relationship between GEF biodiversity index and per capita income, while there is flat/no relationship between carbon emissions and economic growth, and between forest biodiversity and economic growth models. FDI inflows and trade openness both reduce carbon emissions while population density and biofuel consumption increase carbon emissions and decrease GEF biodiversity index. Trade openness supports to increases GEF biodiversity index while it decreases forest biodiversity index and biofuel consumption in a region.

     

Roadmap for climate alliance economies to vision 2030: retrospect and lessons

The United Nations Climate Conference 25, held in December 2019, reached a significant agreement against implementing the Paris agreement come 2020. Bound by the contract, 189 countries who are party to the deal agreed to constrain worldwide temperature to ascend to 1.5° Celsius. To this end, the present study attempts to investigate the readiness of selected countries in the European Union to implement the agreement, which will better the quality of the global environment. In line with this, this study appraises the connection between economic growth, renewable and non-renewable energy consumption, on emissions in 11 countries in the European Union from 1990 to 2016. The study utilises the Pooled Mean Group-Auto Regressive Distributed Lag (PMG-ARDL) model estimator and Dumitrescu and Hurlin Panel Causality analysis to analyse the long-run and short-run impact and direction of causality among these factors, respectively. The long-run study's empirical results show a U-shaped Environmental Kuznets Curve (EKC) and a negative connection between renewable energy use and emissions in the EU-11 countries. In the short-run, non-renewable energy use worsens CO₂ emissions while renewable energy use leads to a fall in emissions. Similarly, causality tests show a feedback mechanism between emissions and renewable energy use and between non-renewable energy and renewable use. Also, there is unidirectional causality from income to CO₂ emissions, non-renewable energy use to CO₂ emissions. The investigation recommends an expanded proportion of renewable energy sources in the EU countries’ energy mix to cut down on emissions.

     

Life cycle energy use,costs, and greenhouse gas emission of broiler farms in different production systems in Iran—a case study of Alborz province

In order to achieve sustainable development in agriculture, it is necessary to quantify and compare the energy, economic, and environmental aspects of products. This paper studied the energy, economic, and greenhouse gas (GHG) emission patterns in broiler chicken farms in the Alborz province of Iran. We studied the effect of the broiler farm size as different production systems on the energy, economic, and environmental indices. Energy use efficiency (EUE) and benefit-cost ratio (BCR) were 0.16 and 1.11, respectively. Diesel fuel and feed contributed the most in total energy inputs, while feed and chicks were the most important inputs in economic analysis. GHG emission calculations showed that production of 1000 birds produces 19.13 t CO_2-eq and feed had the highest share in total GHG emission. Total GHG emissions based on different functional units were 8.5 t CO_2-eq per t of carcass and 6.83 kg CO_2-eq per kg live weight. Results of farm size effect on EUE revealed that large farms had better energy management. For BCR, there was no significant difference between farms. Lower total GHG emissions were reported for large farms, caused by better management of inputs and fewer bird losses. Large farms with more investment had more efficient equipment, resulting in a decrease of the input consumption. In view of our study, it is recommended to support the small-scale broiler industry by providing subsidies to promote the use of high-efficiency equipment. To decrease the amount of energy usage and GHG emissions, replacing heaters (which use diesel fuel) with natural gas heaters can be considered. In addition to the above recommendations, the use of energy saving light bulbs may reduce broiler farm electricity consumption.     

Conditional effect of governance quality on the finance-environment nexus in a multivariate EKC framework: evidence from the method of moments-quantile regression with fixed-effects models

This paper investigates the mitigating effect of governance quality on the finance-environment nexus in a multivariate EKC framework in 123 selected countries during the 1990–2017 period. We mainly employ the method of moments-quantile regression (MM-QR) with the fixed-effects model, among others. First, the MM-QR estimator reveals that financial development reduces environmental quality more significantly in countries with initially higher levels (the 75^th and 90^th quantiles) of CO₂ emissions than in other countries (the 25^th and 10^th quantiles). Second, the attenuating effect of governance quality on the finance-environment nexus is more remarkable in nations with low initial levels (the 25^th and 10^th quantiles) of CO₂ emissions. Third, we find that the marginal positive effect of financial development on CO₂ emissions is smaller under a good regulatory framework than under corruption control and the rule of law, especially in the top emitters (the 75^th and 90^th quantiles). Fourth, unlike oil, which has a considerable negative impact on the environmental quality of the major emitters, renewable energy usage reduces CO₂ emissions in countries in all quantiles, primarily in the lowest quantiles. Fifth, the findings also show that urbanization dramatically worsens environmental quality in all economies, particularly those in the lowest quantiles. Finally, we confirm that the EKC hypothesis holds in all countries across different quantiles. The study’s final section discusses policy implications for sustainable development in all countries.

     

Effects of urbanization and nonrenewable energy on carbon emission in Africa

This study investigates the impact of urbanization and nonrenewable energy consumption on carbon emissions. The context of the analysis is 54 African Union countries from 1996 to 2019. For estimation, we use panel quantile regression (PQR) and fully modified ordinary least squares (FMOLS). Our regression results demonstrate that there is a positive correlation between urbanization and CO₂ emission. Further, our empirical results confirmed that nonrenewable energy consumption increases environmental pollution in African Union countries. The outcomes demonstrate the EKC hypothesis because at the initial stage of development, when economic growth increases, environmental pollution increases; after a threshold point, environmental pollution decreases as economic growth increases. It can find an inverted U-shaped relationship between economic growth and CO₂ emission. The findings also show that urbanization should be planned; otherwise, it can lead to environmental degradation in the long run. Africa continent takes strict action and builds a blueprint for efficient and effective energy production and consumption. The only solution to achieve green growth in Africa is to shift from fossil fuel energy supply to renewable energy supply.

     

Limited provision of roads as a bottleneck on vehicle CO2 emissions in Asia: an international comparison of national trends

This paper explores the relationship between road infrastructure, economic growth and road CO₂ emissions. The basic premise is that many developing nations have achieved sufficient wealth to generate substantial demand for road vehicles, but that actual use is constrained by limited provision of surfaced roads. Our main result is that for comparable levels of income (GDP/capita), CO₂ emissions per length of paved road are far higher in rapidly developing Asia as compared to the USA. These findings suggest existence of an 'infrastructure bottleneck', that when relieved, may influence the future trajectory of road transport CO₂ emissions in developing Asia.     

A global prospective of environmental degradations: economy and finance

Finance plays a crucial role in a fast-growing economy that can lead to environmental degradation. The present study utilizes balanced panel data of 105 countries for the time span 1980–2016 to investigate empirical linkage among environmental degradations: economy and finance. It also unfolds the nonlinear impact of economy and finance on environmental degradation. Existing literature on environmental issues mainly focuses on individual case studies uncovering particular regions, but the comprehensive analysis is not available. To fill this gap, panels were classified into five divisions: global, regional, income-based, OECD-based, and carbon emission. The cross-sectional dependence test is applied to identify the degree of cross-sectional dependence among concerned 16 divisions. The second-generation panel models (CADF and Westerlund cointegration, DOLS, and DH heterogenous causality) are employed on a sample set to compute to unit root, cointegration, and long-run and short-run dynamics among concerned variables, respectively. The findings infer the inverted EKC and U-shaped EKC in 10 and 3 out of 16 divisions with respect to environmental degradation—economy nexus, respectively, while 8 and 2 out of 16 divisions indicate the inverted EKC and U-shaped EKC, respectively, in terms of environmental degradation—finance nexus. In 12 out of 16 divisions, the energy consumption uplifts the CO₂ emissions. The DH causality affirmed a bidirectional causality among economy, finance, and energy consumption, respectively.

     

The nexus between remittances,natural resources,technological innovation,economic growth,and environmental sustainability in Pakistan

Globally, the issues about sustainable development are on the increase. Moreover, these issues are rising every day in Pakistan, as remittances are increasing, technology innovation is ambiguous, natural resources are degraded, and economic expansion might pose serious challenges to the environment. Thus, this research looks at how remittances, natural resources, technological innovation, and economic growth affect carbon dioxide (CO₂₎ emissions in Pakistan by controlling energy consumption and urbanization from 1990 to 2019. The Bayer and Hanck test of combined cointegration discloses a cointegration between remittances, natural resources, technological innovations, economic growth, and CO₂ emissions. Moreover, the autoregressive distributive lag model (ARDL) proposes a significant positive association between remittances and CO₂ emissions in the long run, indicating that the increase in remittances distresses the environmental performance of Pakistan. Our study confirms that natural resources decrease CO₂ emissions while technological advancement, economic progress, energy use, and urbanization increase CO₂ emissions. In addition, the results of robustness checks by employing fully modified ordinary least squares and dynamic ordinary least squares are parallel to the conclusions of ARDL estimations. Furthermore, the frequency causality test results show that remittances, natural resources, technological innovation, economic growth, energy use, and urbanization cause CO₂ emissions at different frequencies. Therefore, to achieve the sustainable development goals, appropriate policy repercussions can be developed toward advanced and environmentally sustainable sources of energy.

     

Use of a vehicle-modelling tool for predicting CO2 emissions in the framework of European regulations for light goods vehicles

The reduction of CO₂ emissions and fuel consumption from road transportation constitutes an important pillar of the EU commitment for implementing the Kyoto Protocol. Efforts to monitor and limit CO₂ emissions from vehicles can effectively be supported by the use of vehicle modelling tools. This paper presents the application of such a tool for predicting CO₂ emissions of vehicles under different operating conditions and shows how the results from simulations can be used for supporting policy analysis and design aiming at further reductions of the CO₂ emissions. For this purpose, the case of light duty goods (N1 category) vehicle CO₂ emissions control measures adopted by the EU is analysed. In order to understand how certain design and operating aspects affect fuel consumption, a number of N1 vehicles were simulated with ADVISOR for various operating conditions and the numerical results were validated against chassis dynamometer tests. The model was then employed for analysing and evaluating the new EU legislative framework that addresses CO₂ emissions from this vehicle class. The results of this analysis have shown the weaknesses of the current regulations and revealed new potential in CO₂ emissions control. Finally the TREMOVE model was used for simulating a possible scenario for reducing CO₂ emissions at fleet level.     

The impact of CO2 capture in the power and heat sector on the emission of SO2, NOx,particulate matter,volatile organic compounds and NH3 in the European Union

This study quantifies the trade-offs and synergies between climate and air quality policy objectives for the European power and heat (P&H) sector. An overview is presented of the expected performance data of CO₂ capture systems implemented at P&H plants, and the expected emission of key air pollutants, being: SO₂, NO_X, NH₃, volatile organic compounds (VOCs) and particulate matter (PM). The CO₂ capture systems investigated include: post-combustion, oxyfuel combustion and pre-combustion capture.For all capture systems it was found that SO₂, NO_x and PM emissions are expected to be reduced or remain equal per unit of primary energy input compared to power plants without CO₂ capture. Increase in primary energy input as a result of the energy penalty for CO₂ capture may for some technologies and substances result in a net increase of emissions per kWh output. The emission of ammonia may increase by a factor of up to 45 per unit of primary energy input for post-combustion technologies. No data are available about the emission of VOCs from CO₂ capture technologies.A simple model was developed and applied to analyse the impact of CO₂ capture in the European P&H sector on the emission level of key air pollutants in 2030. Four scenarios were developed: one without CO₂ capture and three with one dominantly implemented CO₂ capture system, varying between: post-combustion, oxyfuel combustion and pre-combustion.The results showed a reduction in GHG emissions for the scenarios with CO₂ capture compared to the baseline scenario between 12% and 20% in the EU 27 region in 2030. NO_x emissions were 15% higher in the P&H sector in a scenario with predominantly post-combustion and lower when oxyfuel combustion (?16%) or pre-combustion (?20%) were implemented on a large scale. Large scale implementation of the post-combustion technology in 2030 may also result in significantly higher, i.e. increase by a factor of 28, NH₃ emissions compared to scenarios with other CO₂ capture options or without capture. SO₂ emissions were very low for all scenarios that include large scale implementation of CO₂ capture in 2030, i.e. a reduction varying between 27% and 41%. Particulate Matter emissions were found to be lower in the scenarios with CO₂ capture. The scenario with implementation of the oxyfuel technology showed the lowest PM emissions followed by the scenario with a significant share allocated to pre-combustion, respectively ?59% and ?31%. The scenario with post-combustion capture resulted in PM emissions varying between 35% reduction and 26% increase.     

The growth response of Alternanthera philoxeroides in a simulated post-combustion emission with ultrahigh [CO2] and acidic pollutants

Although post-combustion emissions from power plants are a major source of air pollution, they contain excess CO₂ that could be used to fertilize commercial greenhouses and stimulate plant growth. We addressed the combined effects of ultrahigh [CO₂] and acidic pollutants in flue gas on the growth of Alternanthera philoxeroides. When acidic pollutants were excluded, the biomass yield of A. philoxeroides saturated near 2000 μmol mol⁻¹ [CO₂] with doubled biomass accumulation relative to the ambient control. The growth enhancement was maintained at 5000 μmol mol⁻¹ [CO₂], but declined when [CO₂] rose above 1%, in association with a strong photosynthetic inhibition. Although acidic components (SO₂ and NO₂) significantly offset the CO₂ enhancement, the aboveground yield increased considerably when the concentration of pollutants was moderate (200 times dilution). Our results indicate that using excess CO₂ from the power plant emissions to optimize growth in commercial green house could be viable.     

Does energy consumption contribute to environmental pollutants? evidence from SAARC countries

The objective of the study is to examine the causal relationship between energy consumption and environmental pollutants in selected South Asian Association for Regional Cooperation (SAARC) countries, namely, Bangladesh, India, Nepal, Pakistan, and Srilanka, over the period of 1975–2011. The results indicate that energy consumption acts as an important driver to increase environmental pollutants in SAARC countries. Granger causality runs from energy consumption to environmental pollutants, but not vice versa, except carbon dioxide (CO₂) emissions in Nepal where there exists a bidirectional causality between CO₂ and energy consumption. Methane emissions in Bangladesh, Pakistan, and Srilanka and extreme temperature in India and Srilanka do not Granger cause energy consumption via both routes, which holds neutrality hypothesis. Variance decomposition analysis shows that among all the environmental indicators, CO₂ in Bangladesh and Nepal exerts the largest contribution to changes in electric power consumption. Average precipitation in India, methane emissions in Pakistan, and extreme temperature in Srilanka exert the largest contribution.     

Biomass consumption and CO2, CO and main hydrocarbon gas emissions in an Amazonian forest clearing fire

Biomass consumption and CO₂, CO and hydrocarbon gas emissions in an Amazonian forest clearing fire are presented and discussed. The experiment was conducted in the arc of deforestation, near the city of Alta Floresta, state of Mato Grosso, Brazil. The average carbon content of dry biomass was 48% and the estimated average moisture content of fresh biomass was 42% on wet weight basis. The fresh biomass and the amount of carbon on the ground before burning were estimated as 528 t ha^?1 and 147 t ha^?1, respectively. The overall biomass consumption for the experiment was estimated as 23.9%. A series of experiment in the same region resulted in average efficiency of 40% for areas of same size and 50% for larger areas. The lower efficiency obtained in the burn reported here occurred possibly due to rain before the experiment. Excess mixing ratios were measured for CO₂, CO, CH₄, C₂–C₃ aliphatic hydrocarbons, and PM_2.5. Excess mixing ratios of CH₄ and C₂–C₃ hydrocarbons were linearly correlated with those of CO. The average emission factors of CO₂, CO, CH₄, NMHC, and PM_2.5 were 1,599, 111.3, 9.2, 5.6, and 4.8 g kg^?1 of burned dry biomass, respectively. One hectare of burned forest released about 117,000 kg of CO₂, 8100 kg of CO, 675 kg of CH₄, 407 kg of NMHC and 354 kg of PM_2.5.     

Idle Emissions from Heavy-Duty Diesel Vehicles: Review and Recent Data

Abstract

Heavy-duty diesel vehicle idling consumes fuel and reduces atmospheric quality, but its restriction cannot simply be proscribed, because cab heat or air-conditioning provides essential driver comfort. A comprehensive tailpipe emissions database to describe idling impacts is not yet available. This paper presents a substantial data set that incorporates results from the West Virginia University transient engine test cell, the E-55/59 Study and the Gasoline/Diesel PM Split Study. It covered 75 heavy-duty diesel engines and trucks, which were divided into two groups: vehicles with mechanical fuel injection (MFI) and vehicles with electronic fuel injection (EFI). Idle emissions of CO, hydrocarbon (HC), oxides of nitrogen (NO_x), particulate matter (PM), and carbon dioxide (CO₂) have been reported. Idle CO₂ emissions allowed the projection of fuel consumption during idling. Test-to-test variations were observed for repeat idle tests on the same vehicle because of measurement variation, accessory loads, and ambient conditions. Vehicles fitted with EFI, on average, emitted [~20 g/hr of CO, 6 g/hr of HC, 86 g/hr of NO_x, 1 g/hr of PM, and 4636 g/hr of CO₂ during idle. MFI equipped vehicles emitted ~35 g/hr of CO, 23 g/hr of HC, 48 g/hr of NO_x, 4 g/hr of PM, and 4484 g/hr of CO₂, on average, during idle. Vehicles with EFI emitted less idleCO, HC, and PM, which could be attributed to the efficient combustion and superior fuel atomization in EFI systems. Idle NO_x, however, increased with EFI, which corresponds with the advancing of timing to improve idle combustion. Fuel injection management did not have any effect on CO₂ and, hence, fuel consumption. Use of air conditioning without increasing engine speed increased idle CO₂, NO_x, PM, HC, and fuel consumption by 25% on average. When the engine speed was elevated from 600 to 1100 revolutions per minute, CO₂ and NO_x emissions and fuel consumption increased by >150%, whereas PM and HC emissions increased by ~100% and 70%, respectively. Six Detroit Diesel Corp. (DDC) Series 60 engines in engine test cell were found to emit less CO, NO_x, and PM emissions and consumed fuel at only 75%of the level found in the chassis dynamometer data. This is because fan and compressor loads were absent in the engine test cell.